Assessing yield stability of pearl millet and rice cropping systems across West Africa using long-term experiments and a modeling approach.

Long-term field experiments (LTEs) provide invaluable insights into temporal yield patterns of agronomic interventions. However, the number of LTEs and agronomic management options tested withing these experiments remain limited compared to the diversity of farming systems in West Africa. Well-teste...

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Main Authors: Louis Kouadio, Kristina Fraser, Ali Ibrahim, Kazuki Saito, Fatondji Dougbedji, Kalimuthu Senthilkumar
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2025-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0317170
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author Louis Kouadio
Kristina Fraser
Ali Ibrahim
Kazuki Saito
Fatondji Dougbedji
Kalimuthu Senthilkumar
author_facet Louis Kouadio
Kristina Fraser
Ali Ibrahim
Kazuki Saito
Fatondji Dougbedji
Kalimuthu Senthilkumar
author_sort Louis Kouadio
collection DOAJ
description Long-term field experiments (LTEs) provide invaluable insights into temporal yield patterns of agronomic interventions. However, the number of LTEs and agronomic management options tested withing these experiments remain limited compared to the diversity of farming systems in West Africa. Well-tested crop models may be used to identify crop management strategies with high temporal yield stability. This study examines the yield stability of pearl millet and rice under various management options in West Africa, utilizing both experimental and modeling approaches. The Agricultural Production Systems Simulator (APSIM) for pearl millet and rice were calibrated and tested for locally-recommended varieties using LTE data from Niger (pearl millet) and Senegal (rice). Yield stability was evaluated with multiple metrics, including the adjusted coefficient of variation, the sustainable yield index, and the Finlay-Wilkinson regression coefficient. Both APSIM models exhibited a strong performance for grain yield, with Willmott's indices of agreement at 0.74 for pearl millet and 0.90 for rice, and absolute root mean square errors of 0.19 and 1.20 Mg ha-1, respectively. The models effectively reproduced yield stability patterns across a variety of management options including planting date, planting density, fertilizer treatments, and residue retention. Combining fertilizer applications with crop residue retention enhanced yield stability in pearl millet, while season-specific nitrogen management strategies reduced yield variability in rice. Our study underscores the potential of well-tested crop models to complement LTEs in investigating pearl millet and rice yield stability, offering actionable insights for agronomic intensification strategies to enhance productivity and sustainability.
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spelling doaj-art-79f6f38d30774a35ac096e3349ccaf822025-08-20T03:25:34ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01205e031717010.1371/journal.pone.0317170Assessing yield stability of pearl millet and rice cropping systems across West Africa using long-term experiments and a modeling approach.Louis KouadioKristina FraserAli IbrahimKazuki SaitoFatondji DougbedjiKalimuthu SenthilkumarLong-term field experiments (LTEs) provide invaluable insights into temporal yield patterns of agronomic interventions. However, the number of LTEs and agronomic management options tested withing these experiments remain limited compared to the diversity of farming systems in West Africa. Well-tested crop models may be used to identify crop management strategies with high temporal yield stability. This study examines the yield stability of pearl millet and rice under various management options in West Africa, utilizing both experimental and modeling approaches. The Agricultural Production Systems Simulator (APSIM) for pearl millet and rice were calibrated and tested for locally-recommended varieties using LTE data from Niger (pearl millet) and Senegal (rice). Yield stability was evaluated with multiple metrics, including the adjusted coefficient of variation, the sustainable yield index, and the Finlay-Wilkinson regression coefficient. Both APSIM models exhibited a strong performance for grain yield, with Willmott's indices of agreement at 0.74 for pearl millet and 0.90 for rice, and absolute root mean square errors of 0.19 and 1.20 Mg ha-1, respectively. The models effectively reproduced yield stability patterns across a variety of management options including planting date, planting density, fertilizer treatments, and residue retention. Combining fertilizer applications with crop residue retention enhanced yield stability in pearl millet, while season-specific nitrogen management strategies reduced yield variability in rice. Our study underscores the potential of well-tested crop models to complement LTEs in investigating pearl millet and rice yield stability, offering actionable insights for agronomic intensification strategies to enhance productivity and sustainability.https://doi.org/10.1371/journal.pone.0317170
spellingShingle Louis Kouadio
Kristina Fraser
Ali Ibrahim
Kazuki Saito
Fatondji Dougbedji
Kalimuthu Senthilkumar
Assessing yield stability of pearl millet and rice cropping systems across West Africa using long-term experiments and a modeling approach.
PLoS ONE
title Assessing yield stability of pearl millet and rice cropping systems across West Africa using long-term experiments and a modeling approach.
title_full Assessing yield stability of pearl millet and rice cropping systems across West Africa using long-term experiments and a modeling approach.
title_fullStr Assessing yield stability of pearl millet and rice cropping systems across West Africa using long-term experiments and a modeling approach.
title_full_unstemmed Assessing yield stability of pearl millet and rice cropping systems across West Africa using long-term experiments and a modeling approach.
title_short Assessing yield stability of pearl millet and rice cropping systems across West Africa using long-term experiments and a modeling approach.
title_sort assessing yield stability of pearl millet and rice cropping systems across west africa using long term experiments and a modeling approach
url https://doi.org/10.1371/journal.pone.0317170
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